An electrocardiogram (ECG) represents the electrical activity of a patient's heart (see FIG. 2). In general, cardiac monitoring and resuscitation devices use the ECG waveform to determine the condition of a patient's heart. Using sophisticated algorithms, these devices analyze the heart's rhythm to determine if the patient requires therapy. More particularly, automatic external defibrillators (AEDs) use these algorithms to determine if a patient's rhythm is shockable, such as in the case of ventricular fibrillation (see FIG. 3) or high-rate ventricular tachycardia. AEDs also use these algorithms to determine if a patient's rhythm is non-shockable, such as where the ECG waveform contains QRS complexes (i.e., where a series of deflections in an electrocardiogram represents electrical activity generated by ventricular depolarization prior to contraction of the ventricles) or where the patient is experiencing fine VF (below the shockable threshold) (see FIG. 4) or asystole (see FIG. 5).
One common problem with analyzing a patient's rhythm is the introduction of an artifact signal into the ECG. It is difficult for cardiac devices and monitoring devices to distinguish common artifact signals from the underlying rhythm in the ECG signal.
An artifact signal can be introduced by CPR or by motion of the patient during respiration or transport. Such CPR artifact signals originate at the patient's electrode-skin interface when the rescuer compresses the patient's chest. If the device analyzing the patient's rhythms has large electrode pads, such as an AED, the rescuer may touch the pad when performing chest compressions, thereby further aggravating the problem of misleading artifacts.
One specific area of concern is with low cost AEDs and monitoring devices. These devices must analyze the patient's rhythm without some explicit indication of the events causing the artifact signals described above. In addition, these low cost devices may lack the sophisticated electronics, sensors and/or other resources which may be used to detect these artifact signals.
In some instances, e.g., where CPR is performed correctly, the artifact signal is generally sinusoidal in appearance (FIG. 6A). However, if CPR is performed by a layperson or performed during transport, the artifact signal superimposed over a patient's underlying non-shockable ECG rhythm may appear shockable to the analyzing device. In some specific cases, the resulting rhythm may begin to look like ventricular fibrillation (FIG. 6B). The analyzing device may misinterpret the rhythm as shockable and prompt the rescuer to “Stand Clear” and stop performing CPR. Then, the device analyzes the ECG without the artifact signal, determines that the rhythm is non-shockable, and the result is that the rescuer is delayed in performing the necessary CPR therapy. As is well known in the art, delays in performing CPR on a cardiac arrest victim may compromise the outcome of a successful resuscitation.
In cases where significant patient motion creates an artifact signal, the super-imposed ECG rhythm may also appear shockable. As is well known to those skilled in the art, certain motion environments, such as those of fixed-wing aircraft or helicopters, can introduce a vibration at a resonant or harmonic frequency which is related to the fundamental frequency of the source (i.e., the aircraft engine), and this can sometimes cause the monitoring equipment to falsely report a shockable event.
Thus, there is a need for a new and low cost approach for detecting the artifact signals introduced by CPR and/or patient motion, whereby to improve determinations of shockable conditions by monitoring devices.